Seminar: Computational Systems Biology, Spring 07

New

• The seminar has been graded. The results can be seen on the 2. floor bulletin board. If you have any questions, visit Juho during his office hours
• Tentative timetable
  

General information

Moderators:  Ari Rantanen, Juho Rousu

The seminar will cover some key areas of systems biology from the computational point of view. Tentative topics

• Reconstruction of biological networks
• Metabolic engineering at system level
  
• Signal transduction
• Protein interaction
  
• Gene regulation
• Global properties of  biological systems
• Integration and visualization of heterogenous data

To obtain 3 credit units (2 study weeks)  a student will

1. give a presentation based on one or few research articles;
2. return a draft of the seminar report based on the same article(s) at least one week before the presentation and the final version of the report one week after the presentation; and
   
3. be an opponent in one presentation given by a fellow student and otherwise participate actively to discussions in the seminar.

Time and place

17.1. - 25.4. 2007, Wednesdays, 14 - 16 , C221
Click here for timetable

Articles

Presentations can be based on the following articles. (From Here you'll find instructions to obtain an access to the articles from your home computer. The instructions are in Finnish. OpenVPN software required for the access can be downloaded from here.)

Reconstruction of biological networks (1 presentation)

• Florence d’Alch´e–Buc, Vincent Schachter: Modeling and identification of biological networks. Proc. Intl. Symposium on Applied Stochastic Models and Data Analysis (ASMDA 2005), Brest, France (2005), 167-179.

Reconstruction of metabolic networks (1 - 5 presentations)

• Christof Francke, Roland J. Siezen, Bas Teusink: Reconstructing the metabolic network of a bacterium from its genome. Trends in Microbiology, 13 (11) 2005, 550 - 558. (See also Andrei Osterman and Ross Overbeek: Missing genes in metabolic pathways: a comparative genomics approach. Current Opinion in Chemical Biology, Volume 7, Issue 2, April 2003, Pages 238-251.)
• Michelle L Green, Peter D Karp: A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases. BMC Bioinformatics 2004, 5:76. 
  
• Markus J Herrgård, Stephen S Fong, and Bernhard Ø Palsson: Identification of Genome-Scale Metabolic Network Models Using Experimentally Measured Flux Profiles. PLoS Comput Biol. 2006 July; 2(7): e72.
• Simon Borger, Wolfram Liebermeister, Edda Klipp: Prediction of Enzyme Kinetic Parameters Based on Statistical Learning. Genome Informatics 17(1): 80–87 (2006).
• Luca Pireddu, Brett Poulin, Duane Szafron, Paul Lu, and David S. Wishart: Pathway Analyst—Automated MetabolicPathway Prediction. Computational Intelligence in Bioinformatics and Computational Biology, 2005. CIBCB '05. (See also Luca Pireddu, Duane Szafron, Paul Lu and Russell Greiner: The Path-A metabolic pathway prediction web server. Nucleic Acids Research, 2006, Vol. 34, Web Server issue.)
  
• Gille C, Hoffmann S, Holzhutter, H. G.:  Combining bioinformatics resources for the structural modelling of eukaryotic metabolic networks. Genome Inform. 2005;16(1):223-32.<>

Reconstruction of genetic interaction networks (1 - 5 presentations)

• Shen-Orr SS, Milo R, Mangan S, Alon U.:  Network motifs in the transcriptional regulation network of Escherichia coli. Nat Genet. 2002 May;31(1):64-8. Epub 2002 Apr 22. AND  Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U.: Network motifs: simple building blocks of complex networks.  Science. 2002 Oct 25;298(5594):824-7. See also comments to the article and the articles commenting and extending  the original work: Ofer Meshi, Tomer Shlomi, and Eytan Ruppin: Evolutionary conservation and over-representation of functionally enriched network patterns in the yeast regulatory network. BMC Systems Biology 2007, 1:1 AND Aurélien Mazurie, Samuel Bottani and Massimo Vergassola: An evolutionary and functional assessment of regulatory network motifs. Genome Biology 2005, 6:R35.
  
• Paul François, Vincent Hakim:  Design of genetic networks with specified functions by evolution in silico. PNAS 2004;101;580-585.
• James C. Liao, Riccardo Boscolo, Young-Lyeol Yang, Linh My Tran, Chiara Sabatti,  Vwani P. Roychowdhury: Network component analysis: Reconstruction of regulatory signals in biological systems. PNAS 2003;100;15522-15527.
• Ryan Kelley, Trey Ideker: Systematic interpretation of genetic interactions using protein networks. Nature Biotechnology (2005) 23(5), 561-566.
• E. Segal, H. Wang and D. Koller: Discovering molecular pathways from protein interaction and gene expression data. Bioinformatics Vol. 19 Suppl. 1 2003, pages i264–i272.
• E. Segal et al.:  Module Networks: Identifying Regulatory Modules and Their Condition-Specific Regulators from Gene Expression Data. Nature Genetics (2003), 34(2), 166-176.
• Anshuman Gupta, Jeffrey D. Varner, Costas D. Maranas: Large-scale inference of the transcriptional regulation of Bacillus subtilis. Computers and Chemical Engineering 29 (2005) 565–576.
• Maciag et al.: Systems-level analyses identify extensive coupling among gene expression machines. Molecular Systems Biology (2006) doi:10.1038/msb4100045.
  

Metabolic engineering at system level (0 - 2 presentations)

• Priti Pharkya, Anthony P. Burgard, and Costas D. Maranas: OptStrain: A computational framework for redesign of microbial production systems. Genome Res. 2004 14: 2367-2376. AND Priti Pharkya, Anthony P. Burgard, Costas D. Maranas:  Exploring the Overproduction of Amino Acids Using the Bilevel Optimization Framework OptKnock. Biotechnology and Bioengineering, 84, 887-899.
• Priti Pharkya, Costas D. Maranas:  An optimization framework for identifying reaction activation/inhibition or elimination candidates for overproduction in microbial systems. Metabolic Engineering 8 (2006) 1–13.

Global properties and robustness of biological systems (1 - 5 presentations)

• Albert-László Barabási & Zoltán N. Oltvai: NETWORK BIOLOGY: UNDERSTANDING THE CELL'S FUNCTIONAL ORGANIZATION . Nature Reviews Genetics 5, 101-113 (2004).  (get the paper through NELLI)
• Dongxiao Zhu, Zhaohui S Qin: Structural comparison of metabolic networks in selected single cell organisms. BMC Bioinformatics 2005, 6:8.
  
• Nizar N. Batada, Laurence D. Hurst, Mike Tyers: Evolutionary and Physiological Importance of Hub Proteins. PLoS Comput Biol 2(7): e88.
• Han et al.:  Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature 430, 88-93(1 July 2004).
• John Rachlin, Dikla Dotan Cohen, Charles Cantor, Simon Kasif:  Biological context networks: a mosaic view of the interactome. Molecular Systems Biology 2 doi:10.1038/msb4100103 Published online: 28 November 2006 Article number: 66.

Metabolomics (1 - 3 presentations)

• M. Scholz, S. Gatzek, A. Sterling, O. Fiehn, J. Selbig: Metabolite fingerprinting: detecting biological features by independent component analysis. Bioinformatics Vol. 20 no. 15 2004, pages 2447–2454.
• Tobias Kind, Oliver Fiehn: Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm. BMC Bioinformatics 2006, 7:234.
• R. Steuer, J. Kurths, O. Fiehn, W. Weckwerth: Observing and interpreting correlations in metabolomic networks. Bioinformatics, Vol. 19 no. 8 2003, pages 1019–1026. (See also R. Steuer: On the analysis and interpretation of correlations in metabolomic data. BRIEFINGS IN BIOINFORMATICS. VOL 7 NO 2. ISI-158. Get the paper through NELLI)

Integration and visualization of heterogenous data (0 -2 presentations)

• Hwang et al.:  A data integration methodology for systems biology. PNAS 2005;102;17296-17301 AND Hwang et al.: A data integration methodology for systems biology: Experimental verification. PNAS 2005;102;17302-17307.
• Hucka et al.:  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics. 2003 Mar 1;19(4):524-31. AND Hiroaki Kitano, Akira Funahashi, Yukiko Matsuoka, Kanae Oda: Using process diagrams for the graphical representation of biological networks. Nature Biotechnology  23, 961 - 966 (2005). (AND Michael L. Blinov, Jin Yang, James R. Faeder, William S. Hlavacek: Depicting signaling cascades. NATURE BIOTECHNOLOGY VOLUME 24 NUMBER 2 FEBRUARY 2006.)
• Suzanne M. Paley, Peter D. Karp: The Pathway Tools cellular overview diagram and Omics Viewer. Nucleic Acids Research, 2006, Vol. 34, No. 13 3771–3778.
  
• Björn H Junker, Christian Klukas, Falk Schreiber: VANTED: A system for advanced data analysis and visualization in
  the context of biological networks. BMC Bioinformatics 2006, 7:109.

Seminar report

• Seminar report will follow the guide lines given for an essay in the course scientific writing.
• about 10 pages long
• Abstract, proper citations (unlike in this page!)
  
• The draft of the seminar report will be send to Ari via e-mail (ajrantan@cs.helsinki.fi) in pdf format no later than one week before the oral presentation.
• The draft will be linked to the home page of  the seminar.
• THE AUDIENCE WILL READ THE SEMINAR REPORTS BEFORE THE ORAL PRESENTATIONS.
• The presenter will edit the report besed on the comments given by the opponent, moderators and other audience. The final version of the report will be send to Ari no later than one week after the oral presentation.
  
• The report will be written in English.
  

Oral presentation

• The length of the oral presentation is 45 - 60 minutes.
• The presentation is followed (and  also interrupted)  by a lively discussion, catalyzed by the opponent.
• The language of the presentation is English.
  

Being an opponent

• The moderators of the seminar will name 1 - n opponents for each presentation.
• Everyone will be an opponent for at least one presentation.
• The opponent will give written constructive feedback (comments, questions) to the draft of the seminar report no later than 48 hours before the oral presentation. The feedback will be send via e-mail to the moderators and to the presenter.
• Is there something unclear in the draft?
• What are the most/less interesting parts of the report considering the upcoming oral presentation?
  
• Also positive feedback is welcomed!
• For Finnish presenters comments will be written either in Finnish or in English. For foreign presenters comments will be written in English.
  
• The discussion after the oral presentation starts with a couple of comments and questions by the opponent.
  

Instructions for presenters

Here are some general guidelines you should follow when preparing your seminar report and presentation.

• Remember what you have learned in the course scientific writing. Especially, check an example for formatting your report. Also, you can load CS Latex style from the www-page of the course.
  
• Your primary task is  to give an understandable and complete presentation about  the computational methods applied in the original articles. Sometimes the computation is described in the appendices or in different papers. Read these, too!
• Remember to give an introduction to general computational methods (ICA, MILP, linear programming...) used in the articles. If the method is not covered in the obligatory Bachelor level CS courses or earlier in the seminar, you should give at least a brief overview to the method.
  
• Do not be afraid of  presenting your own conclusions, as long as they are based on the "scientific method".
• Make sure that the audience sufficiently understands the biological problem that is being solved before you go into techical stuff. Introduce  biological terminology before use.
• Give examples and illustrations.
• Make sure that the audience understands the experimental setting when you describe empirical results.
  
• Do not base your report or your presentation to a single article. Follow the references in the primary article(s), use search engines etc.
• Do not copy-paste original articles to the report. Write a commentary: discuss the soundness and the practicality of the methods presented in the papers, compare the presented methods to the methods introduced earlier in the seminar or some other known methods, comment on the validity of experimental settings etc.
  
• Try to be constructive in your feedback to the presenter. Every  presentation has something good and something that can be improved.